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» On the Noise Model of Support Vector Machines Regression
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BMCBI
2011
13 years 3 months ago
Support vector machines-based identification of alternative splicing in Arabidopsis thaliana from whole-genome tiling arrays
Background: Alternative splicing (AS) is a process which generates several distinct mRNA isoforms from the same gene by splicing different portions out of the precursor transcript...
Johannes Eichner, Georg Zeller, Sascha Laubinger, ...
IVC
2006
120views more  IVC 2006»
13 years 8 months ago
Facial pose from 3D data
The distribution of the apparent 3D shape of human faces across the view-sphere is complex, owing to factors such as variations in identity, facial expression, minor occlusions an...
Ajit Rajwade, Martin D. Levine
ICML
2007
IEEE
14 years 9 months ago
Most likely heteroscedastic Gaussian process regression
This paper presents a novel Gaussian process (GP) approach to regression with inputdependent noise rates. We follow Goldberg et al.'s approach and model the noise variance us...
Kristian Kersting, Christian Plagemann, Patrick Pf...
JCST
2008
138views more  JCST 2008»
13 years 8 months ago
Predicting Chinese Abbreviations from Definitions: An Empirical Learning Approach Using Support Vector Regression
In Chinese, phrases and named entities play a central role in information retrieval. Abbreviations, however, make keyword-based approaches less effective. This paper presents an em...
Xu Sun, Houfeng Wang, Bo Wang 0003
ICMLA
2003
13 years 10 months ago
Robust Support Vector Machines for Anomaly Detection in Computer Security
— Using the 1998 DARPA BSM data set collected at MIT’s Lincoln Labs to study intrusion detection systems, the performance of robust support vector machines (RVSMs) was compared...
Wenjie Hu, Yihua Liao, V. Rao Vemuri